{"id":"W3162609213","doi":"10.7557/3.5794","title":"Report of the NAMMCO-ICES Workshop on Seal Modelling (WKSEALS 2020)","year":2021,"lang":"en","type":"article","venue":"NAMMCO Scientific Publications","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Natural Environment Research Council; Sight Research UK","keywords":"Vital rates; Bayesian probability; Population; Population model; Bayesian inference; Markov chain Monte Carlo; Statistics; Statistical model; Computer science; Geography; Fishery; Biology; Mathematics; Demography; Population growth","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01325405,0.001959613,0.0009623973,0.001533583,0.000645945,0.003156247,0.003131147,0.002661857,0.03014986],"category_scores_gemma":[0.007967032,0.0006793831,0.002051666,0.0008634387,0.0006547961,0.003351169,0.006021393,0.002281112,0.01097559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001746874,"about_ca_system_score_gemma":0.005740152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01748448,"about_ca_topic_score_gemma":0.01298027,"domain_scores_codex":[0.998304,0.0006366029,0.0001070805,0.0001797267,0.0005819893,0.0001905324],"domain_scores_gemma":[0.9963971,0.000674311,0.0001664939,0.0003904766,0.001273385,0.001098151],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005120806,0.0002422351,0.003390471,0.0007805064,0.0001399978,0.0003533121,0.0004277691,0.03313341,0.003084719,0.01802875,0.7319916,0.2079152],"study_design_scores_gemma":[0.000054452,0.0001290979,0.002639344,0.001163166,0.00006242863,0.0001213378,0.0002410869,0.02620601,0.001577961,0.01447356,0.953275,0.00005650218],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.05294345,0.06973794,0.3770147,0.1139772,0.06035488,0.001872184,0.05757328,0.01357479,0.2529515],"genre_scores_gemma":[0.1489726,0.04995103,0.3190147,0.01191668,0.008377081,0.00227124,0.1734105,0.009505362,0.2765808],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.03014986,"threshold_uncertainty_score":0.1008613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04519524032576954,"score_gpt":0.2816063653526447,"score_spread":0.2364111250268752,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}